

˰ is uniquely known for, and has always put a premium on, demonstrating rather than merely promising breakthroughs in quantum computing.
When we unveiled the first H-Series quantum computer in 2020, not only did we pioneer the world-leading quantum processors, but we also went the extra mile. We included industry leading comprehensive benchmarking to ensure that any expert could independently verify our results. Since then, our computers have maintained the lead against all competitors in performance and transparency. Today our System Model H2 quantum computer with 56 qubits is the most powerful quantum computer available for industry and scientific research – and the most benchmarked.
More recently, in a period where we upgraded our H2 system from 32 to 56 qubits and demonstrated the scalability of our QCCD architecture, we also , and announced that we had achieved “three 9’s” fidelity, enabling real gains in fault-tolerance – which we proved within months as we demonstrated the most reliable logical qubits in the world with our partner Microsoft.
We don’t just promise what the future might look like; we demonstrate it.
Today, at Quantum World Congress, we shared how recent developments by our integrated hardware and software teams have, yet again, accelerated our technology roadmap. It is with the confidence of what we’ve already demonstrated that we can uniquely announce that by the end of this decade ˰ will achieve universal fully fault-tolerant quantum computing, built on foundations such as a universal fault-tolerant gate set, high fidelity physical qubits uniquely capable of supporting reliable logical qubits, and a fully-scalable architecture.

We also demonstrated, with Microsoft, what rapid acceleration looks like with the creation of 12 highly reliable logical qubits – tripling the number from just a few months ago. Among other demonstrations, we supported Microsoft to create the first ever chemistry simulation using reliable logical qubits combined with Artificial Intelligence (AI) and High-Performance Computing (HPC), producing results within chemical accuracy. This is a critical demonstration of what Microsoft has called “the path to a Quantum Supercomputer”.
˰’s H-Series quantum computers, Powered by Honeywell, were among the first devices made available via Microsoft Azure, where they remain available today. Building on this, we are excited to share that ˰ and Microsoft have completed integration of ˰’s InQuanto™ computational quantum chemistry software package with Azure Quantum Elements, the AI enabled generative chemistry platform. The integration mentioned above is accessible to customers participating in a private preview of Azure Quantum Elements, which can be requested from Microsoft and ˰.
We created a short video on the importance of logical qubits, which you can see here:
These demonstrations show that we have the tools to drive progress towards scientific and industrial advantage in the coming years. Together, we’re demonstrating how quantum computing may be applied to some of humanity’s most pressing problems, many of which are likely only to be solved with the combination of key technologies like AI, HPC, and quantum computing.
Our credible roadmap draws a direct line from today to hundreds of logical qubits - at which point quantum computing, possibly combined with AI and HPC, will outperform classical computing for a range of scientific problems.
“The collaboration between ˰ and Microsoft has established a crucial step forward for the industry and demonstrated a critical milestone on the path to hybrid classical-quantum supercomputing capable of transforming scientific discovery.” – Dr. Krysta Svore – Technical Fellow and VP of Advanced Quantum Development for Microsoft Azure Quantum
What we revealed today underlines the accelerating pace of development. It is now clear that enterprises need to be ready to take advantage of the progress we can see coming in the next business cycle.
The industry consensus is that the latter half of this decade will be critical for quantum computing, prompting many companies to develop roadmaps signalling their path toward error corrected qubits. In their entirety, ˰’s technical and scientific advances accelerate the quantum computing industry, and as we have shown today, reveal a path to universal fault-tolerance much earlier than expected.
Grounded in our prior demonstrations, we now have sufficient visibility into an accelerated timeline for a highly credible hardware roadmap, making now the time to release an update. This provides organizations all over the world with a way to plan, reliably, for universal fully fault-tolerant quantum computing. We have shown how we will scale to more physical qubits at fidelities that support lower error rates (made possible by QEC), with the capacity for “universality” at the logical level. “Universality” is non-negotiable when making good on the promise of quantum computing: if your quantum computer isn’t universal everything you do can be efficiently reproduced on a classical computer.
“Our proven history of driving technical acceleration, as well as the confidence that globally renowned partners such as Microsoft have in us, means that this is the industry’s most bankable roadmap to universal fully fault-tolerant quantum computing,” said Dr. Raj Hazra, ˰’s CEO.
Before the end of the decade, our quantum computers will have thousands of physical qubits, hundreds of logical qubits with error rates less than 10-6, and the full machinery required for universality and fault-tolerance – truly making good on the promise of quantum computing.
˰ has a proven history of achieving our technical goals. This is evidenced by our leadership in hardware, software, and the ecosystem of developer tools that make quantum computing accessible. Our leadership in quantum volume and fidelity, our consistent cadence of breakthrough publications, and our collaboration with enterprises such as Microsoft, showcases our commitment to pushing the boundaries of what is possible.
We are now making an even stronger public commitment to deliver on our roadmap, ushering the industry toward the era of universal fully fault-tolerant quantum computing this decade. We have all the machinery in place for fault-tolerance with error rates around 10-6, meaning we will be able to run circuits that are millions of gates deep – putting us on a trajectory for scientific quantum advantage, and beyond.
˰, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. ˰’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, ˰ leads the quantum computing revolution across continents.
While there is ongoing debate around the pace of quantum computing’s development, a more grounded way to assess progress is through concrete demonstrations of foundational algorithms at meaningful scale. In this context, Mitsui & Co. and Mitsubishi Electric are taking a pragmatic view of quantum progress—focusing on how close the field is to executing core algorithmic primitives that underpin many potential industrial applications, rather than relying on abstract milestones or timelines.
, the industrial giants teamed up with ˰ to measure how close we are to running the Quantum Fourier Transform (QFT), a widely-used algorithmic primitive, at scales necessary for industrial applications. In the process, the team successfully ran one of the largest instances of the approximate QFT ever demonstrated. This achievement matters because the QFT is an essential primitive that underpins many of the quantum algorithms expected to deliver practical advantages.
You may have heard of the (classical) Fourier transform (FT), due to its ubiquity throughout modern computing. The FT is essential in everything from image analysis to data compression, with almost limitless applications in between. The quantum Fourier transform (QFT) is similar; it’s used in everything from chemistry to finance.
Because the QFT is a foundational primitive underpinning many quantum algorithms, demonstrating it at larger scales and higher fidelity is a practical way to measure quantum computing readiness. This is exactly the type of benchmarking that organizations should consider to understand where today’s systems are useful, and to see how fault-tolerant approaches are progressing. Ultimately, algorithm-level benchmarking like this is one of the most useful ways to understand not just where we are, but where we are going.
Primitives like Fourier Transform are so widespread because they simplify problems by transforming them into something that is easier to deal with. At ˰, not only are they crucial for industrial applications but they can also simplify algorithms, making them possible to run now instead of later. This ‘transformational’ approach extends beyond the QFT - other transforms exist, and we have even invented our own quantum-native transforms.
Using our ˰ quantum computer and Guppy language, the joint team explored running the QFT on both physical qubits and on logical qubits, showing that fault tolerance is progressing quickly. Running the QFT on 98 physical qubits; the paper shows a clear progression from previous results.
Then, using the Steane code, one of the best-studied quantum error correcting codes, the team used ˰’ 98 physical qubits to form 12 logical qubits, successfully running the QFT with the mechanisms of quantum error correction interwoven into the algorithm. This marks a crucial step forward for the field.
Taken together, these results provide a more concrete lens through which to view progress in quantum computing: not as abstract projections, but as measurable advances in the execution of foundational algorithms at increasing scale. By benchmarking the Quantum Fourier Transform on both physical and logical qubits, Mitsui & Co. and Mitsubishi Electric are helping to clarify what today’s hardware can already achieve, and where fault-tolerant approaches begin to extend those limits.
More broadly, the organizations best positioned to benefit from quantum computing will be those that focus on these foundational capabilities early, and use them to build a clear, evidence-based understanding of how the technology fits into their business goals.
It is believed that unlocking answers to some of the most complex scientific and industrial problems will require the seamless integration of high-performance computing (HPC), generative AI (GenAI), and quantum computing. Toward this goal, ˰, NVIDIA, and a major pharmaceutical company have successfully demonstrated the first step in a proof-of-principle framework designed to connect these three distinct computing paradigms for industrially relevant computational chemistry.
This milestone, enabled by three industry leaders and experts in their respective domains, serves as a foundational capability that could support the development of future hybrid quantum-AI workflows to help optimize industrial research and development (R&D).
The potential value is a path toward more automated, repeatable, and scalable workflows for translating chemistry problems into executable quantum programs—capabilities that could eventually make hybrid computing easier to deploy in industrial R&D.
The framework, termed Generative Quantum AI (GenQAI), involved a quantum computer simulating a pharmaceutical compound using programming instructions generated by an AI model, which itself was trained on quantum data that was simulated using HPC.
While the vision for GenQAI explores how future industrial simulation workflows might be optimized by training AI models using quantum data derived directly from a quantum computer, the framework currently consists of four main technical steps:
The core novelty of this development lies within the process of the framework itself. In this proof-of-principle experiment, an AI model fine-tuned on simulated quantum data generated circuits that were successfully executed and validated on ˰’s ˰ system. Rather than delivering an immediate commercial advantage, this achievement establishes a credible, verifiable baseline for how HPC, AI, and quantum computing can function in tandem.
The validation of the framework represents an early step toward the goal of developing scalable architectures for the pharmaceutical industry.
With a shared view toward eventually scaling the framework for pharmaceutical R&D applications, the researchers simulated a pharmaceutical compound: imipramine. This anti-depressant was chosen because it serves as a model compound for drug degradation and shelf-life studies, which are standard components of the pharmaceutical R&D lifecycle.
Developing hybrid infrastructure that enterprises may adopt requires a deep, coordinated effort among domain experts. As such, this successful test highlights the value of combining the strengths of a quantum computing hardware and software leader (˰), with a hybrid-quantum classical platform (NVIDIA), and a leading enterprise end-user to build and test future computing capabilities for industrial chemistry.
Although demonstrated on a pharmaceutical compound, the architecture could eventually inform similar molecular-simulation workflows in sectors such as energy, agriculture, advanced materials, and electronics. At this stage, it provides a reference for further testing and development.
here to explore the full technical details of this demonstration and contact our team to learn more about joining ˰’s enterprise partner network.

˰ is pleased to announce that applications are now open for the ˰ SG Grand Challenge 2026, a global innovation challenge designed to bring together researchers, developers, scientists and innovators to explore practical applications of quantum computing.
Organized by ˰ and supported by Singapore's National Quantum Office and Aqora, the three-month program aims to foster collaboration across academia, industry and the quantum developer community while supporting the continued growth of Singapore's quantum ecosystem.
Participants will work in teams to develop solutions across a range of challenge areas, including chemistry and molecular simulation, optimization, AI for quantum systems, quantum error correction, condensed matter and materials science, and open innovation. Throughout the program, participants will have access to mentoring, technical enablement and ˰ quantum computing resources.
Selected finalist teams will be invited to present their work at the Grand Finale hosted in Singapore before representatives from academia, and industry. The event will celebrate innovative applications of quantum computing while providing an opportunity for participants to engage with Singapore's growing quantum community.
The ˰ SG Grand Challenge welcomes participants from around the world. Whether you are an experienced quantum researcher or beginning your quantum computing journey, the program offers an opportunity to collaborate, learn and contribute to the development of practical quantum applications.
Applications are now open. Spaces are limited and subject to review and approval.